Add fitted values, residuals, and other common outputs to an augment call

augment_columns is intended for use in the internals of augment methods only and is exported for developers extending the broom package. Please instead use augment() to appropriately make use of the functionality in augment_columns().

Usage

augment_columns(
  x,
  data,
  newdata = NULL,
  type,
  type.predict = type,
  type.residuals = type,
  se.fit = TRUE,
  ...
)

Arguments

x: a model
data: original data onto which columns should be added
newdata: new data to predict on, optional
type: Type of prediction and residuals to compute
type.predict: Type of prediction to compute; by default same as type
type.residuals: Type of residuals to compute; by default same as type
se.fit: Value to pass to predict's se.fit, or NULL for no value. Ignored for model types that do not accept an se.fit argument
...: extra arguments (not used)

Details

Note that, in the case that a residuals() or influence() generic is not implemented for the supplied model x, the function will fail quietly.